scholarly journals Novel Implementations of Clutter and Target Discrimination Using Threshold Skewness Method

2021 ◽  
Vol 38 (4) ◽  
pp. 1079-1085
Author(s):  
Thottempudi Pardhu ◽  
Vijay Kumar
Keyword(s):  
Long Range ◽  
Imaging Techniques ◽  
Research Work ◽  
Decomposition Technique ◽  
Tracking Method ◽  
Target Discrimination ◽  
Image Tracking ◽  
Single Value Decomposition ◽  
Value Decomposition ◽  
Wall Imaging

Now a day’s defence applications associated to novel, army and military war fields are required wall imaging discrimination. As of now many wall-imaging techniques are designed but cannot discriminate the target and clutter with accurate working. Therefore, a novel advance wall image tracking method is required for differentiate the clutter and human target. In this research work single value decomposition technique is used to estimate the range bin behind the wall target. In order to track the target and clutter single-value-decomposition (SVD) is not sufficient, so that along this SVD, threshold skewness (TS) method has been presented. Combination of SVD-TS giving the accurate long range-bin sensing and directed the human’s targets. SVD-TS method is a statistical scheme, which can realise the amplitude ranges through large number of range-bin scans. This technique improves the accuracy by 98.6%, skewness by 8%, and normalised power by 98.9%. These SVD-TS method is more efficient and compete with existed techniques.

An Automatic Text Summarization Method with the Concern of Covering Complete Formation

2020 ◽  
Vol 13 (5) ◽  
pp. 977-986
Author(s):  
Srinivasa Rao Kongara ◽  
Dasika Sree Rama Chandra Murthy ◽  
Gangadhara Rao Kancherla
Keyword(s):  
Research Method ◽  
Research Work ◽  
Fuzzy Rule ◽  
Text Summarization ◽  
Document Summarization ◽  
Summarization Method ◽  
Overall Evaluation ◽  
Multiple Documents ◽  
Rule System ◽  
Value Decomposition

Background: Text summarization is the process of generating a short description of the entire document which is more difficult to read. This method provides a convenient way of extracting the most useful information and a short summary of the documents. In the existing research work, this is focused by introducing the Fuzzy Rule-based Automated Summarization Method (FRASM). Existing work tends to have various limitations which might limit its applicability to the various real-world applications. The existing method is only suitable for the single document summarization where various applications such as research industries tend to summarize information from multiple documents. Methods: This paper proposed Multi-document Automated Summarization Method (MDASM) to introduce the summarization framework which would result in the accurate summarized outcome from the multiple documents. In this work, multi-document summarization is performed whereas in the existing system only single document summarization was performed. Initially document clustering is performed using modified k means cluster algorithm to group the similar kind of documents that provides the same meaning. This is identified by measuring the frequent term measurement. After clustering, pre-processing is performed by introducing the Hybrid TF-IDF and Singular value decomposition technique which would eliminate the irrelevant content and would result in the required content. Then sentence measurement is one by introducing the additional metrics namely Title measurement in addition to the existing work metrics to accurately retrieve the sentences with more similarity. Finally, a fuzzy rule system is applied to perform text summarization. Results: The overall evaluation of the research work is conducted in the MatLab simulation environment from which it is proved that the proposed research method ensures the optimal outcome than the existing research method in terms of accurate summarization. MDASM produces 89.28% increased accuracy, 89.28% increased precision, 89.36% increased recall value and 70% increased the f-measure value which performs better than FRASM. Conclusion: The summarization processes carried out in this work provides the accurate summarized outcome.

scholarly journals Through-Wall Image Enhancement Based on Singular Value Decomposition

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Muhammad Mohsin Riaz ◽  
Abdul Ghafoor
Keyword(s):  
Singular Value Decomposition ◽  
Image Enhancement ◽  
Visual Inspection ◽  
Signal To Noise Ratio ◽  
Singular Values ◽  
Singular Value ◽  
Information Theoretic ◽  
Value Decomposition ◽  
Suppress Noise ◽  
Wall Imaging

Singular value decomposition and information theoretic criterion-based image enhancement is proposed for through-wall imaging. The scheme is capable of discriminating target, clutter, and noise subspaces. Information theoretic criterion is used with conventional singular value decomposition to find number of target singular values. Furthermore, wavelet transform-based denoising is performed (to further suppress noise signals) by estimating noise variance. Proposed scheme works also for extracting multiple targets in heavy cluttered through-wall images. Simulation results are compared on the basis of mean square error, peak signal to noise ratio, and visual inspection.

A Two Components Approach for Long Range Remote Raman and Laser-Induced Breakdown (LIBS) Spectroscopy Using Low Laser Pulse Energy

2018 ◽  
Vol 73 (3) ◽  
pp. 320-328 ◽  
Author(s):  
Anupam K. Misra ◽  
Tayro E. Acosta-Maeda ◽  
John N. Porter ◽  
Genesis Berlanga ◽  
Dalton Muchow ◽  
...  
Keyword(s):  
Laser Pulse ◽  
Long Range ◽  
Raman Spectra ◽  
Homeland Security ◽  
Pulse Energy ◽  
Laser Energy ◽  
Research Effort ◽  
Research Work ◽  
High Signal ◽  
Laser Induced Breakdown

The remote detection of chemicals using remote Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) is highly desirable for homeland security and NASA planetary exploration programs. We recently demonstrated Raman spectra with high signal-to-noise ratio of various materials from a 430 m distance during daylight with detection times of 1–10 s, utilizing a 203 mm diameter telescopic remote Raman system and 100 mJ/pulse laser energy at 532 nm for excitation. In this research effort, we describe a simple two-components approach that helps to obtain remote Raman and LIBS spectra of targets at distance of 246 m with 3 mJ/pulse in daytime. The two components of the method are: (1) a small spectroscopy system utilizing 76 mm diameter collection optics; and (2) a small remote lens near the target. Remote Raman spectra of various chemicals are presented here with detection time of 1 s. Remote LIBS spectra of minerals using single laser pulse of 3 mJ/pulse energy from a distance of 246 m are also presented. This research work demonstrates a simple approach that significantly improves remote Raman and LIBS capabilities for long range chemical detection with compact low laser power Raman and LIBS systems.

3D IMAGE RECONSTRUCTION FOR SUBMERGED OBJECTS USING RAMP RESPONSE SIGNATURES

2011 ◽  
Vol 08 (04) ◽  
pp. 825-836
Author(s):  
W. LI
Keyword(s):  
Imaging Techniques ◽  
Research Work ◽  
Acoustic Scattering ◽  
Image Synthesis ◽  
3D Image ◽  
Scattering Problems ◽  
3D Image Reconstruction ◽  
Acoustical Imaging ◽  
Limiting Surface ◽  
Ramp Response

Underwater acoustical imaging techniques and the inverse analysis of acoustic scattering problems have now found many important engineering applications. Based on the physical optics approximation, the ramp response signal can be proven that it is proportional to the profile function of the scatterer, which is defined as the area of cross section of the object perpendicular to the direction of wave propagation. The image synthesis technique named as the approximate limiting surface technique is applied to generated underwater objects by using the ramp responses of the objects. The modification should be made by an iterative procedure which will adjust the parameters of each surface and will yield a result until the profile functions of this generated image at all looking angles are consistent with the input ones. Several typical objects are presented to demonstrate the process of the 3D image generation and the results indicate that the qualities of the final images are quite acceptable. The further research work is to build an automatic iterative mechanism to generate the final image for a submerged object.

A non-cooperative long-range biometric image tracking and recognition (BITAR) method for maritime surveillance

2008 ◽  
Author(s):  
Xiaokun Li ◽  
Genshe Chen ◽  
Erik Blasch ◽  
Harold H. Szu ◽  
Thomas McKenna
Keyword(s):  
Long Range ◽  
Image Tracking ◽  
Maritime Surveillance ◽  
Tracking And Recognition
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